The globe faces an urgent need to close the energy demand-supply gap.Addressing this difficulty requires constructing a Hybrid Renewable Energy System(HRES),which has proven to be the most appropriate solution.HRES al...The globe faces an urgent need to close the energy demand-supply gap.Addressing this difficulty requires constructing a Hybrid Renewable Energy System(HRES),which has proven to be the most appropriate solution.HRES allows for integrating two or more renewable energy resources,successfully addressing the issue of intermittent availability of non-conventional energy resources.Optimization is critical for improving the HRES’s performance parameters during implementation.This study focuses on HRES using solar and biomass as renewable energy supplies and appropriate energy storage technologies.However,energy fluctuations present a problem with the power quality of HRES.To address this issue,the research paper introduces the Generalized Dynamic Progressive Neural Fuzzy Controller(GDPNFC),which regulates power flow within the proposed HRES.Furthermore,a unique approach called Enhanced Multi-Objective Monarch Butterfly Optimization(EMMBO)is used to optimize technical parameters.The simulation tool used in the research work is HOMER(Hybrid Optimization of Multiple Energy Resources)-PRO,and the system’s power quality is assessed using MATLAB 2016.The research paper concludes with comparing the performance of existing systems to the proposed system in terms of power loss and Total Harmonic Distortion(THD).It was established that the proposed technique involving EMMBO outperformed existing methods in technical optimization.展开更多
Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressi...Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressing these shortcomings,thiswork presents a robust 15-level PackedUCell(PUC)inverter topology designed for renewable energy and grid-connected applications.The proposed systemintegrates a sensor less proportional-resonant(PR)controller with an advanced carrier-based pulse width modulation scheme.This approach efficiently balances capacitor voltage,minimizes steady-state error,and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation.Additionally,a novel switching algorithm simplifies the design and implementation,further lowering voltage stress across switches.Extensive simulation results validate the performance under various resistive and resistive-inductive load conditions,demonstrating compliance with IEEE-519 THD standards and robust operation under dynamic changes.The proposed sensorless PR-controlled 15-PUC inverter thus offers a compelling,cost-effective solution for efficient power conversion in next-generation renewable energy systems.展开更多
文摘The globe faces an urgent need to close the energy demand-supply gap.Addressing this difficulty requires constructing a Hybrid Renewable Energy System(HRES),which has proven to be the most appropriate solution.HRES allows for integrating two or more renewable energy resources,successfully addressing the issue of intermittent availability of non-conventional energy resources.Optimization is critical for improving the HRES’s performance parameters during implementation.This study focuses on HRES using solar and biomass as renewable energy supplies and appropriate energy storage technologies.However,energy fluctuations present a problem with the power quality of HRES.To address this issue,the research paper introduces the Generalized Dynamic Progressive Neural Fuzzy Controller(GDPNFC),which regulates power flow within the proposed HRES.Furthermore,a unique approach called Enhanced Multi-Objective Monarch Butterfly Optimization(EMMBO)is used to optimize technical parameters.The simulation tool used in the research work is HOMER(Hybrid Optimization of Multiple Energy Resources)-PRO,and the system’s power quality is assessed using MATLAB 2016.The research paper concludes with comparing the performance of existing systems to the proposed system in terms of power loss and Total Harmonic Distortion(THD).It was established that the proposed technique involving EMMBO outperformed existing methods in technical optimization.
文摘Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressing these shortcomings,thiswork presents a robust 15-level PackedUCell(PUC)inverter topology designed for renewable energy and grid-connected applications.The proposed systemintegrates a sensor less proportional-resonant(PR)controller with an advanced carrier-based pulse width modulation scheme.This approach efficiently balances capacitor voltage,minimizes steady-state error,and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation.Additionally,a novel switching algorithm simplifies the design and implementation,further lowering voltage stress across switches.Extensive simulation results validate the performance under various resistive and resistive-inductive load conditions,demonstrating compliance with IEEE-519 THD standards and robust operation under dynamic changes.The proposed sensorless PR-controlled 15-PUC inverter thus offers a compelling,cost-effective solution for efficient power conversion in next-generation renewable energy systems.
